ACM SIGMIS Database the DATABASE for Advances in Information Systems
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Author(s):  
Hamed Qahri-Saremi ◽  
Isaac Vaghefi ◽  
Ofir Turel

Prior studies have primarily used "variable-centered" perspectives to identify factors underlying user responses to social networking site (SNS) addiction, their predictors and outcomes. This paper extends this perspective by taking a person-centered approach to examine (1) the prototypical subpopulations (profiles) of users' extent of SNS addiction and responses to it, (2) how affiliations with these profiles can explain user behaviors toward SNS use, and (3) how personality traits can predict affiliations with these profiles. To this end, we propose a typological theory of SNS addiction and user responses to it via two empirical, personcentered studies. Study 1 draws on survey data from 188 SNS users to develop a typology of users based on the extent of their SNS addiction and their responses to it. It further examines the relations between affiliation with these profiles and users' SNS discontinuance intention, as a typical behavioral response to SNS addiction. Study 2 uses survey data from 284 SNS users to validate the user typology developed in Study 1 and investigate its relations to users' Big Five personality traits. Our findings shed light on a typology of five prototypical profiles of SNS users-cautious, regular, consonant, dissonant, and hooked-who differ in their extent of SNS addiction and their cognitive, emotional, and behavioral responses to it. Our findings also demonstrate how Big Five personality traits can predict user affiliations with these prototypical profiles.


Author(s):  
Tom Stafford ◽  
Mohamed Tazkarji
Keyword(s):  

It's been a long year-and-a-half or since the initial outbreak arose down here in Louisiana, right after Mardi Gras 2020, February. New Orleans and its widely attended Mardi Gras looked to be the "spreader event" of our region, it seemed like.


Author(s):  
Fred Niederman

A minimalist view of theory will render it more accessible for a wider range of research questions. More accessible theory will facilitate constant improvement between representations predicting particular relationships among entities of interest in IS and observations of those relationships in practice. This is needed in IS to direct research energy toward knowledge that can lead to more effective and helpful interventions for computing technology stakeholders. The paper also addresses a range of anomalies created by prevailing traditional views of theory, particularly regarding the distinction between theory existence and theory level of support. Discussion includes identifying barriers to conversion to this view of theory as well as criteria for evaluation of proposed new theory.


Author(s):  
InduShobha Chengalur-Smith ◽  
Saggi Nevo ◽  
Brian Fitzgerald

Open source software (OSS) is increasingly being developed by hybrid teams that consist of a mix of company employees and volunteer developers. While hybrid OSS teams are becoming more prevalent, they also face unique challenges due to the involvement of different constituents. To address those challenges, this paper develops and validates a new organizing model. Specifically, the paper draws on media synchronicity theory (MST) to theorize that hybrid OSS teams would benefit from adopting an organizing model that involves practicing agile methods and using communication tools with multiple symbols sets and high transmission velocity. The paper also extends MST by conceptualizing the theory's key concept of communication convergence as consisting of two distinct dimensions: affective and cognitive convergence. Using primary survey data from hybrid OSS teams, the paper presents empirical evidence that such an organizing model can enhance those teams' affective convergence and cognitive convergence and, in turn, their development productivity and the quality of the software. In addition, the results show that affective convergence has a stronger impact on hybrid OSS teams' performance than cognitive convergence.


Author(s):  
Gaurav Bansal ◽  
Merrill Warkentin

Recently, data breaches, especially insider data breaches, have become increasingly common. However, there is a limited amount of research on the factors associated with the decrease in users' trust in response to these events. In this study, social role theory and socioemotional selectivity theory are applied to understand the role of age (younger and older), biological (male and female) and cultural (masculinity and femininity) gender, and the four dimensions of privacy concern-collection, secondary use, unauthorized access, and error-on initial trust and the corresponding decrease in trust associated with the three trust beliefs of ability, benevolence, and integrity. A scenario-based approach is used to focus on a case study of an insider breach. The findings also provide helpful insights into the comparative roles of trust builders (e.g., reputation and design) and trust crashers (e.g., privacy concerns) in the process of trust building and trust decrease in different demographics (e.g., older and younger, males and females) for overall trust and trusting beliefs. Theoretical, managerial, and social implications are discussed.


Author(s):  
Colleen Carraher-Wolverton ◽  
Jim Burleson

Although initial adoption of an information system has been shown to influence system success, further value can be obtained when end-users move beyond adoption, utilizing more features of the system and integrating it into their work routines. Organizations can increase the post-deployment utilization of their systems by emphasizing continued interaction between developers and end-users. In this study, we develop a research model investigating the influence of shared understanding, faithfulness of appropriation, and consensus on spirit on post-deployment system utilization. Using a sample from a healthcare organization, we show that increased end-user postdeployment interaction with developers supports a shared understanding between the two groups, which ultimately impacts both the routinization and infusion of a system. This study provides a contribution by demonstrating the impact of developer/user interaction in the post-implementation phase of systems development.


Author(s):  
Jun-Hwa Cheah ◽  
Christian Nitzl ◽  
José L. Roldán ◽  
Gabriel Cepeda-Carrion ◽  
Siegfried P. Gudergan

Conditional mediation (CoMe) analysis integrates mediation and moderation analyses to examine and test hypotheses about how mediated relationships vary as a function of context, boundaries, or individual differences. Although CoMe analysis can be a crucial element of empirical studies that seek to advance theory in information systems, applications of such analysis are scarce, in general, and in partial least squares structural equation modeling (PLS-SEM), in particular. This paper clarifies conceptual fundamentals of and develops guidelines for CoMe analysis within the PLS-SEM context. Furthermore, the paper outlines the illustrative use of CoMe analysis in PLS-SEM and presents detailed step-by-step procedures to do so in the PLS-SEM setting. Overall, this paper provides researchers and practitioners with the required knowledge to properly carry out, report, and interpret CoMe analysis in PLS-SEM.


Author(s):  
Xi Yu ◽  
Sam Zaza ◽  
Florian Schuberth ◽  
Jörg Henseler

Studying and modeling theoretical concepts is a cornerstone activity in information systems (IS) research. Researchers have been familiar with one type of theoretical concept, namely behavioral concepts, which are assumed to exist in nature and measured by a set of observable variables. In this paper, we present a second type of theoretical concept, namely forged concepts, which are designed and assumed to emerge within their environment. While behavioral concepts are classically operationalized as latent variables, forged concepts are better specified as emergent variables. Additionally, we propose composite-based structural equation modeling (SEM) as a subtype of SEM that is eminently suitable to analyze models containing emergent variables. We shed light on the composite-based SEM steps: model specification, model identification, model estimation, and model assessment. Then, we present an illustrative example from the domain of IS research to demonstrate these four steps and show how modeling with emergent variables proceeds.


Author(s):  
Tom Stafford ◽  
Deborah J. Armstrong

Friends, Deb Armstrong and I have reached the culmination of our editorial term, and K.D. Joshi of University of Nevada-Reno has been chosen as the new Editor-in-Chief. Professor Joshi is a long-time contributor, Senior Editor, and thought leader in our parent organization, ACM SIGMIS, and its venerable CPR conference. K.D. has a marvelous vision, superb connections with our ACM SIGMIS CPR constituency, and an operational record second to none. She will be a great leader for continuing the growth trajectory of The DATA BASE for Advances in Information Systems.


Author(s):  
Nicholas P. Danks

Researchers are becoming cognizant of the value of conducting predictive analysis using partial least squares structural equation modeling (PLS-SEM) for both the evaluation of overfit and to illustrate the practical value of models. Mediators are a popular mechanism for adding nuance and greater explanatory power to causal models. However, mediators pose a special challenge to generating predictions as they serve a dual role of antecedent and outcome. Solutions for generating predictions from mediated PLS-SEM models have not been suitably explored or documented, nor has there been exploration of whether the added model complexity of such mediators is justified in the light of predictive performance. We address that gap by evaluating methods for generating predictions from mediated models, and propose a simple metric that quantifies the predictive contribution of the mediator (PCM). We conduct Monte Carlo simulations and then apply the methods in an empirical demonstration. We find that there is no simple best solution, but that all three approaches have strengths and weaknesses. Further, the PCM metric performs well to quantify the predictive qualities of the mediator over-and-above the non-mediated alternative. We present guidelines on selecting the most appropriate method and applying PCM for additional evidence to support research conclusions.


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